Semantic Plug & Play - Selbstbeschreibende Hardware für modulare Robotersysteme

Moderne Robotersysteme bestehen aus einer Vielzahl unterschiedlicher Sensoren und Aktuatoren, aus deren Zusammenwirken verschiedene Fähigkeiten entstehen und nutzbar gemacht werden. So kann ein Knickarmroboter über die koordinierte Ansteuerung mehrerer Motoren Gegenstände greifen, oder ein Quadrocopter über Sensoren seine Lage und Position bestimmen. Eine besondere Ausprägung bilden modulare Robotersysteme, in denen sich Sensoren und Aktuatoren dynamisch entfernen, austauschen oder hinzufügen lassen, wodurch auch die verfügbaren Fähigkeiten beeinflusst werden. Die Flexibilität modularer Robotersysteme wird jedoch durch deren eingeschränkte Kompatibilität begrenzt. So existieren zahlreiche proprietäre Systeme, die zwar eine einfache Verwendung ermöglichen aber nur auf eine begrenzte Menge an modularen Elementen zurückgreifen können. Open-Source-Projekte mit einer breiten Unterstützung im Hardwarebereich, wie bspw. die Arduino-Plattform, oder Softwareprojekte, wie das Robot Operating System (ROS) versuchen, eine eben solch breite Kompatibilität zu bieten, erfordern allerdings eine sehr ausführliche Dokumentation der Hardware für die Integration. Das zentrale Ergebnis dieser Dissertation ist ein Technologiestack (Semantic Plug & Play) für die einfache Dokumentation und Integration modularer Hardwareelemente durch Selbstbeschreibungsmechanismen. In vielen Anwendungen befindet sich die Dokumentation üblicherweise verteilt in Textdokumenten, Onlineinhalten und Quellcodedokumentationen. In Semantic Plug & Play wird ein System basierend auf den Technologien des Semantic Web vorgestellt, das nicht nur eben solch vorhandene Dokumentationen vereinheitlicht und kollektiviert, sondern das auch durch eine maschinenlesbare Aufbereitung die Dokumentation in der Prozessdefinition verwendet werden kann. Eine in dieser Dissertation entwickelte Architektur bietet für die Prozessdefinition eine API für objektorientierte Programmiersprachen, in der abstrakte Fähigkeiten verwendet werden können. Mit einem besonderen Fokus auf zur Laufzeit rekonfigurierbare Systeme können damit Fähigkeiten über Anforderungen an aktuelle Hardwarekonfigurationen ausgedrückt werden. So ist es möglich, qualitative und quantitative Eigenschaften als Voraussetzung für Fähigkeiten zu definieren, die erst bei einem Wechsel modularer Hardwareelemente erfüllt werden. Diesem Prinzip folgend werden auch kombinierte Fähigkeiten unterstützt, die andere Fähigkeiten hardwareübergreifend für ihre intrinsische Ausführung nutzen. Für die Kapselung der Selbstbeschreibung auf einzelnen Hardwareelementen werden unterschiedliche Adapter in Semantic Plug & Play unterstützt, wie etwa Mikrocontroller oder X86- und ARM-Systeme. Semantic Plug & Play ermöglicht zudem eine Erweiterbarkeit zu ROS anhand unterschiedlicher Werkzeuge, die nicht nur eine hybride Nutzung erlauben, sondern auch die Komplexität mit modellgetriebenen Ansätzen beherrschbar machen. Die Flexibilität von Semantic Plug & Play wird in sechs Experimenten anhand unterschiedlicher Hardware illustriert. Alle Experimente adressieren dabei Problemstellungen einer übergeordneten Fallstudie, für die ein heterogener Quadrocopterschwarm in hochgradig dynamischen Szenarien eingesetzt und gezielt rekonfiguriert wird

Towards fully automated inspection of large components with UAVs: offline path planning

Automation mechanisms are increasingly established in the field of visual inspections. UAVs can be used for particularly large components, such as those used in ship production and for critical infrastructures. This paper concentrates on the problem of visual inspection in the field of perspective-dependent route planning. It is shown how the requirements for such a system can be implemented and elaborated. Furthermore we investigate how sensor positions can be calculated offline, based on optical and geometrical requirements and how a trajectory can be planned which contains the found sensor positions for each given area on the component. It is shown how the systems architecture can be designed in order to be able to adapt it to different requirements for the planning of sensor positions and trajectory. The implementation was tested in a simulation environment, evaluated using a benchmark data set and it was shown how above-average results can be achieved on this data set

UAV inspection of large components: indoor navigation relative to structures

The inspection of large structures is increasingly carried out with the help of Unmanned Aerial Vehicles (UAVs). When navigating relative to the structure, multiple data sources can be used to determine the position of the UAV. Examples include track data from an installed camera and sensor data from the orientation sensors of the UAV. This paper deals with the fusion of this data and its use for navigation alongside the structure. For the sensor fusion, a concept is developed using a Kalman filter and evaluated simulatively in a prototype. The calculated position data are also fed into a vector flight control system, which dynamically calculates and flies a trajectory along the component using the potential field method. This is done taking into account obstacles detected by the onboard sensors of the UAV. The established concept is then implemented with the Robot Operating System (ROS) and evaluated simulatively

Towards a real-time capable plug & produce environment for adaptable factories

Industrial manufacturing is currently undergoing a transformation from mass production with inflexible production systems to individual production with adaptable cells. In order to ensure this adaptability of these systems, technologies such as plug & produce are needed, to integrate, modify and remove devices at runtime. Therefor an exact description of the system, the products and the capabilities / skills of the devices is essential as well as a network for communication between the devices. Deterministic data transmission is particularly important for distributed control systems. We propose an architecture for plug & produce mechanisms with hard real-time capable communication paths between the cyber-physical components using OPC UA PubSub over TSN and the ability to load and execute real-time critical tasks at runtime

ROSSi a graphical programming interface for ROS 2

The Robot Operating System (ROS) offers developers a large number of ready-made packages for developing robot programs. The multitude of packages and the different interfaces or adapters is also the reason why ROS projects often tend to become confusing. Concepts of model-driven software development using a domain-specific modeling language could counteract this and at the same time speed up the development process of such projects. This is investigated in this paper by transferring the core concepts from ROS 2 into a graphical programming interface. Elements of established graphical programming tools are compared and approaches from modeling languages such as UML are used to create a novel approach for graphical development of ROS projects. The resulting interface is evaluated through the development of a project built on ROS, and the approach shows promise towards facilitating work with the Robot Operating System

UAV inspection of large components: determination of alternative inspection points and online route optimization

Automation is playing an increasing role in the field of quality assurance. For the visual inspection of larger assemblies such as aircraft fuselages or ship hulls, the use of UAVs is an option. This paper deals with one aspect of the UAV-supported inspection of assemblies in production. Here, newly added components have to be checked for correct assembly. The planning of the shortest possible route from which all components to be inspected can be viewed as well as the estimation of the UAV’s position relative to the component have already been presented in previous work. We propose strategies that can be used if an inspection point cannot be reached by the UAV or the component to be inspected cannot be seen by the UAV’s camera from the inspection point. For this purpose, we generate alternative inspection points that can be used if errors occur during the inspection from the original inspection point. To achieve this, we present a metric that can be used to select an alternative inspection point that is as suitable as possible. We conclude by demonstrating how this strategy works by evoking different failure cases in a simulated environment

Architecture for emergency control of autonomous UAV ensembles

Applying unmanned aerial vehicles (UAV) has benefits for many different use-cases. Existing implementations of ground control stations (GCS) to manage UAVs in such scenarios already provide some support for the operation of multi-unit systems, i.e., ensembles. However, since they are usually designed for the operation of only one copter at once, this is often not sufficient to react quickly in dangerous situations, e.g., search and rescue scenarios. To address this problem, we propose an approach for easy observation and control of complete autonomous UAV ensembles: The Intention of our approach is to greatly reduce the number of personnel required for the operation of an UAV ensemble. Thereby, we generate the possibility for rapid intervention in potentially dangerous situations in order to prevent damage to the UAVs and the environment. In this paper, we present a software architecture for this safety-critical multi UAV ground control station including a fully implemented prototype which we also tested in a realistic environment